Highlights Propose the CACC-OIFT strategy to dynamically optimize information flow topology (IFT) for CACC. Under CACC-OIFT, vehicles dynamically deactivate/activate “send” functionality of their V2V communication devices. CACC-OIFT consists of an IFT optimization model and an adaptive Proportional- Derivative controller. CACC-OIFT enhances string stability of platoon control in an unreliable V2V communication context.

    Abstract Emergent cooperative adaptive cruise control (CACC) strategies being proposed for platoon formation in the connected autonomous vehicle (CAV) context mostly assume idealized fixed information flow topologies (IFTs) for the platoon, implying guaranteed vehicle-to-vehicle (V2V) communications for the IFT assumed. In reality, V2V communications are unreliable due to failures resulting from communication-related constraints such as interference and information congestion. Since CACC strategies entail continuous information broadcasting, communication failures can occur in congested CAV traffic networks, leading to a platoon’s IFT varying dynamically. To explicitly factor IFT dynamics and to leverage it to enhance the performance of CACC strategies, this study proposes the idea of dynamically optimizing the IFT for CACC, labeled the CACC-OIFT strategy. Under CACC-OIFT, the vehicles in the platoon cooperatively determine in real-time which vehicles will dynamically deactivate or activate the “send” functionality of their V2V communication devices to generate IFTs that optimize the platoon performance in terms of string stability under the ambient traffic conditions. The CACC-OIFT consists of an IFT optimization model and an adaptive Proportional-Derivative (PD) controller. Given the adaptive PD controller with a two-predecessor-following scheme, and the ambient traffic conditions and the platoon size just before the start of a time period, the IFT optimization model determines the optimal IFT that maximizes the expected string stability in terms of the energy of speed oscillations. This expectation is because each IFT has specific degeneration scenarios whose probabilities are determined by the communication failure probabilities for that time period based on the ambient traffic conditions. The optimal IFT is deployed for that time period, and the adaptive PD controller continuously determines the car-following behaviors of the vehicles based on the unfolding degeneration scenario for each time instant within that period. The effectiveness of the proposed CACC-OIFT is validated through numerical experiments in NS-3 based on NGSIM field data. The results indicate that the proposed CACC-OIFT can significantly enhance the string stability of platoon control in an unreliable V2V communication context, outperforming CACCs with fixed IFTs or with passive adaptive schemes for IFT dynamics.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Cooperative adaptive cruise control for connected autonomous vehicles by factoring communication-related constraints


    Contributors:
    Wang, Chaojie (author) / Gong, Siyuan (author) / Zhou, Anye (author) / Li, Tao (author) / Peeta, Srinivas (author)


    Publication date :

    2019-04-12


    Size :

    22 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles using Spring Damping Energy Model

    Xie, Songtao / Hu, Junyan / Ding, Zhengtao et al. | BASE | 2022

    Free access

    Resilient Cooperative Adaptive Cruise Control for Autonomous Vehicles Using Machine Learning

    Boddupalli, Srivalli / Rao, Akash Someshwar / Ray, Sandip | IEEE | 2022




    COOPERATIVE ADAPTIVE CRUISE CONTROL FOR ELECTRIFIED POWERTRAIN VEHICLES

    BORHAN HOSEINALI / FRAZIER TIMOTHY R | European Patent Office | 2023

    Free access